[11186] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17226] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11186] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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[17525] | 22 | using System.Collections.Generic;
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[11245] | 23 | using System.IO;
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[11190] | 24 | using System.Linq;
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[17525] | 25 | using System.Threading;
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| 26 | using HEAL.Attic;
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[16692] | 27 | using HeuristicLab.Analysis;
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[11186] | 28 | using HeuristicLab.Common;
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| 29 | using HeuristicLab.Core;
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| 30 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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| 31 | using HeuristicLab.Optimization;
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[16692] | 32 | using HeuristicLab.Optimization.Operators;
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[11187] | 33 | using HeuristicLab.Parameters;
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[11189] | 34 | using HeuristicLab.Problems.Instances;
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[11261] | 35 | using HeuristicLab.Problems.Instances.Types;
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[17525] | 36 | using HeuristicLab.Problems.TravelingSalesman;
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[11186] | 37 |
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| 38 | namespace HeuristicLab.Problems.Orienteering {
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[13173] | 39 | [Item("Orienteering Problem (OP)", "Represents a single-objective Orienteering Problem.")]
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[12721] | 40 | [Creatable(CreatableAttribute.Categories.CombinatorialProblems, Priority = 115)]
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[16723] | 41 | [StorableType("0B8DB4A4-F183-4368-86C6-C51289B183D2")]
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[17525] | 42 | public sealed class OrienteeringProblem : IntegerVectorProblem,
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| 43 | IProblemInstanceConsumer<OPData>, IProblemInstanceConsumer<TSPData>, IProblemInstanceConsumer<CVRPData> {
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[11186] | 44 |
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[17525] | 45 | [Storable] public ValueParameter<IOrienteeringProblemData> OrienteeringProblemDataParameter { get; private set; }
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| 46 | [Storable] public OptionalValueParameter<OrienteeringSolution> BestKnownSolutionParameter { get; private set; }
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| 47 | [Storable] private IResultParameter<OrienteeringSolution> BestOrienteeringSolutionParameter { get; set; }
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| 48 | public IResultDefinition<OrienteeringSolution> BestOrienteeringSolution => BestOrienteeringSolutionParameter;
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[11186] | 49 |
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[17525] | 50 | public IOrienteeringProblemData OrienteeringProblemData {
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| 51 | get { return OrienteeringProblemDataParameter.Value; }
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| 52 | set { OrienteeringProblemDataParameter.Value = value; }
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[11187] | 53 | }
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[17525] | 54 | public OrienteeringSolution BestKnownSolution {
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[11187] | 55 | get { return BestKnownSolutionParameter.Value; }
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| 56 | set { BestKnownSolutionParameter.Value = value; }
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| 57 | }
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| 58 |
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[11186] | 59 | [StorableConstructor]
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[16723] | 60 | private OrienteeringProblem(StorableConstructorFlag _) : base(_) {
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[11186] | 61 | }
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| 62 | private OrienteeringProblem(OrienteeringProblem original, Cloner cloner)
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| 63 | : base(original, cloner) {
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[17525] | 64 | OrienteeringProblemDataParameter = cloner.Clone(original.OrienteeringProblemDataParameter);
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| 65 | BestKnownSolutionParameter = cloner.Clone(original.BestKnownSolutionParameter);
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| 66 | BestOrienteeringSolutionParameter = cloner.Clone(original.BestOrienteeringSolutionParameter);
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[11186] | 67 | }
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| 68 | public override IDeepCloneable Clone(Cloner cloner) {
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| 69 | return new OrienteeringProblem(this, cloner);
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| 70 | }
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| 71 | public OrienteeringProblem()
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[17525] | 72 | : base(new IntegerVectorEncoding("Route")) {
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| 73 | Parameters.Add(OrienteeringProblemDataParameter = new ValueParameter<IOrienteeringProblemData>("OP Data", "The main parameters for the orienteering problem.", new OrienteeringProblemData()));
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| 74 | Parameters.Add(BestKnownSolutionParameter = new OptionalValueParameter<OrienteeringSolution>("BestKnownSolution", "The best known solution of this Orienteering instance."));
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| 75 | Parameters.Add(BestOrienteeringSolutionParameter = new ResultParameter<OrienteeringSolution>("Best Orienteering Solution", "The best so far solution found."));
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| 76 | Maximization = true;
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[11186] | 77 |
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| 78 | InitializeOperators();
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| 79 | }
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| 80 |
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[17525] | 81 | public override ISingleObjectiveEvaluationResult Evaluate(IntegerVector solution, IRandom random, CancellationToken cancellationToken) {
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| 82 | var data = OrienteeringProblemData;
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| 83 | var score = CalculateScore(data, solution);
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| 84 | var travelCosts = CalculateTravelCosts(data, solution);
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| 85 | var quality = CalculateQuality(data, score, travelCosts);
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[11190] | 86 |
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[17525] | 87 | return new SingleObjectiveEvaluationResult(quality);
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[11190] | 88 | }
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| 89 |
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[17525] | 90 | public static double CalculateQuality(IOrienteeringProblemData data, double score, double travelCosts) {
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| 91 | if (travelCosts > data.MaximumTravelCosts) return data.MaximumTravelCosts - travelCosts; // negative excessive distance
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| 92 | return score;
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[11190] | 93 | }
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[17525] | 94 | public static double CalculateScore(IOrienteeringProblemData data, IEnumerable<int> solution) {
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| 95 | return solution.Sum(t => data.GetScore(t));
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[11190] | 96 | }
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[17525] | 97 | public static double CalculateTravelCosts(IOrienteeringProblemData data, IntegerVector solution) {
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[17533] | 98 | var distance = data.GetPathDistance(solution, closed: false);
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[17525] | 99 | distance += (solution.Length - 2) * data.PointVisitingCosts;
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| 100 | return distance;
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[11328] | 101 | }
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[17525] | 102 | public static double CalculateTravelCosts(IOrienteeringProblemData data, IList<int> solution) {
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[17533] | 103 | var distance = data.GetPathDistance(solution, closed: false);
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[17525] | 104 | distance += (solution.Count - 2) * data.PointVisitingCosts;
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| 105 | return distance;
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[11186] | 106 | }
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| 107 |
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[17525] | 108 | public override void Analyze(IntegerVector[] vectors, double[] qualities, ResultCollection results, IRandom random) {
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| 109 | base.Analyze(vectors, qualities, results, random);
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| 110 | var data = OrienteeringProblemData;
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[11190] | 111 |
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[17526] | 112 | var best = GetBestSolution(vectors, qualities).Item1;
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| 113 | var score = CalculateScore(OrienteeringProblemData, best);
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| 114 | var travelCosts = CalculateTravelCosts(OrienteeringProblemData, best);
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[17525] | 115 | var quality = CalculateQuality(OrienteeringProblemData, score, travelCosts);
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| 116 |
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[17526] | 117 | if (double.IsNaN(BestKnownQuality) || IsBetter(quality, BestKnownQuality)) {
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| 118 | BestKnownQuality = quality;
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| 119 | BestKnownSolutionParameter.ActualValue = data.GetSolution((IntegerVector)best.Clone(), quality, score, travelCosts);
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[11190] | 120 | }
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[17525] | 121 | var bestSoFar = BestOrienteeringSolutionParameter.ActualValue;
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| 122 |
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[17526] | 123 | if (bestSoFar == null || IsBetter(quality, bestSoFar.Quality.Value)) {
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| 124 | bestSoFar = data.GetSolution((IntegerVector)best.Clone(), quality, score, travelCosts);
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[17525] | 125 | BestOrienteeringSolutionParameter.ActualValue = bestSoFar;
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| 126 | }
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[11186] | 127 | }
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[17525] | 128 | public static double CalculateInsertionCosts(IOrienteeringProblemData data, IList<int> path, int insertPosition, int point) {
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[17533] | 129 | double detour = data.GetDistance(path[insertPosition - 1], point) + data.GetDistance(point, path[insertPosition]);
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[17525] | 130 | detour += data.PointVisitingCosts;
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[17533] | 131 | detour -= data.GetDistance(path[insertPosition - 1], path[insertPosition]);
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[17525] | 132 | return detour;
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[11186] | 133 | }
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[17525] | 134 | public static double CalculateReplacementCosts(IOrienteeringProblemData data, IList<int> path, int replacePosition, int point) {
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[17533] | 135 | double detour = data.GetDistance(path[replacePosition - 1], point) + data.GetDistance(point, path[replacePosition + 1]);
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| 136 | detour -= data.GetDistance(path[replacePosition - 1], path[replacePosition]) + data.GetDistance(path[replacePosition], path[replacePosition + 1]);
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[17525] | 137 | return detour;
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[11186] | 138 | }
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[17525] | 139 | public static double CalculateRemovementSaving(IOrienteeringProblemData data, IList<int> path, int removePosition) {
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[17533] | 140 | double saving = data.GetDistance(path[removePosition - 1], path[removePosition]);
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| 141 | saving += data.GetDistance(path[removePosition], path[removePosition + 1]);
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| 142 | saving -= data.GetDistance(path[removePosition - 1], path[removePosition + 1]);
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[17525] | 143 | saving += data.PointVisitingCosts;
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| 144 | return saving;
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| 145 | }
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[11191] | 146 |
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[17525] | 147 | protected override void OnEncodingChanged() {
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| 148 | base.OnEncodingChanged();
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| 149 | ParameterizeOperators();
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| 150 | }
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[11191] | 151 |
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[17525] | 152 | protected override void OnEvaluatorChanged() {
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| 153 | base.OnEvaluatorChanged();
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| 154 | ParameterizeOperators();
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[11186] | 155 | }
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[17525] | 156 |
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[11186] | 157 | private void InitializeOperators() {
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[17525] | 158 | Encoding.SolutionCreator = new GreedyOrienteeringTourCreator() {
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| 159 | OrienteeringProblemDataParameter = { ActualName = OrienteeringProblemDataParameter.Name }
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| 160 | };
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[11191] | 161 |
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[17525] | 162 | Operators.Add(new OrienteeringLocalImprovementOperator() {
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| 163 | OrienteeringProblemDataParameter = { ActualName = OrienteeringProblemDataParameter.Name }
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| 164 | });
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| 165 | Operators.Add(new OrienteeringShakingOperator() {
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| 166 | OrienteeringProblemDataParameter = { ActualName = OrienteeringProblemDataParameter.Name }
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| 167 | });
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[16692] | 168 | Operators.Add(new QualitySimilarityCalculator());
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| 169 | Operators.Add(new PopulationSimilarityAnalyzer(Operators.OfType<ISolutionSimilarityCalculator>()));
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| 170 |
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[11191] | 171 | ParameterizeOperators();
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[11186] | 172 | }
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[17525] | 173 |
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[11186] | 174 | private void ParameterizeOperators() {
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[11194] | 175 | foreach (var op in Operators.OfType<OrienteeringLocalImprovementOperator>()) {
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[17525] | 176 | op.IntegerVectorParameter.ActualName = Encoding.Name;
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| 177 | op.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
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[11194] | 178 | }
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[11195] | 179 | foreach (var op in Operators.OfType<OrienteeringShakingOperator>()) {
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[17525] | 180 | op.IntegerVectorParameter.ActualName = Encoding.Name;
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[11195] | 181 | }
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[16692] | 182 | foreach (var similarityCalculator in Operators.OfType<ISolutionSimilarityCalculator>()) {
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[17525] | 183 | similarityCalculator.SolutionVariableName = Encoding.Name;
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[16692] | 184 | similarityCalculator.QualityVariableName = Evaluator.QualityParameter.ActualName;
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| 185 | }
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[11186] | 186 | }
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| 187 |
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[11325] | 188 | #region Instance consuming
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[11277] | 189 | public void Load(OPData data) {
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| 190 | if (data.Coordinates == null && data.Distances == null)
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| 191 | throw new InvalidDataException("The given instance specifies no coordinates or distance matrix!");
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| 192 | if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
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[11245] | 193 | throw new InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates.");
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| 194 |
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| 195 | // Clear old solutions
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| 196 | BestKnownSolution = null;
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| 197 |
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[11189] | 198 | Name = data.Name;
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| 199 | Description = data.Description;
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| 200 |
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[17529] | 201 | var tsp = TSP.GetDataFromInstance(data);
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[17525] | 202 | OrienteeringProblemData = new OrienteeringProblemData(tsp, data.StartingPoint, data.TerminalPoint, data.Scores, data.MaximumDistance, data.PointVisitingCosts);
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[11189] | 203 | }
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[11261] | 204 |
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[11277] | 205 | public void Load(TSPData data) {
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| 206 | if (data.Coordinates == null && data.Distances == null)
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| 207 | throw new InvalidDataException("The given instance specifies no coordinates or distance matrix!");
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| 208 | if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
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[11261] | 209 | throw new InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates.");
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| 210 |
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| 211 | // Clear old solutions
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| 212 | BestKnownSolution = null;
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| 213 |
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| 214 | Name = data.Name;
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| 215 | Description = data.Description;
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| 216 |
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| 217 |
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[17529] | 218 | var tsp = TSP.GetDataFromInstance(data);
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[17525] | 219 | var avgDist = 0.0;
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| 220 | for (var i = 0; i < data.Dimension - 1; i++)
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| 221 | for (var j = i + 1; i < data.Dimension; j++)
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| 222 | avgDist += tsp.GetDistance(i, j);
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| 223 | avgDist /= (data.Dimension - 1) * data.Dimension / 2.0;
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[11261] | 224 |
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[17525] | 225 | OrienteeringProblemData = new OrienteeringProblemData(tsp, 0, data.Dimension - 1,
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| 226 | Enumerable.Repeat(1.0, data.Dimension).ToArray(), 5 * avgDist, 0);
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[11261] | 227 | }
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[11277] | 228 |
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| 229 | public void Load(CVRPData data) {
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| 230 | if (data.Coordinates == null && data.Distances == null)
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| 231 | throw new InvalidDataException("The given instance specifies no coordinates or distance matrix!");
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| 232 | if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
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| 233 | throw new InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates.");
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| 234 |
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| 235 | // Clear old solutions
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| 236 | BestKnownSolution = null;
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| 237 |
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| 238 | Name = data.Name;
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| 239 | Description = data.Description;
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| 240 |
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[17529] | 241 | var tsp = TSP.GetDataFromInstance(data);
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| 242 | OrienteeringProblemData = new OrienteeringProblemData(tsp, 0, 0, data.Demands, data.Capacity * 2, 0);
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[11277] | 243 | }
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[11325] | 244 | #endregion
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[11186] | 245 | }
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| 246 | } |
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